Generally, a security system has been mostly used for a national security and an industrial security, but is recently used for a personal security and a computer security.
Especially, the development of computer network systems including Internet has brought the problem that a computer network system becomes increasingly vulnerable to attack and therefore individual information is likely to leak out through networking such as electronic commerce, the Internet, etc.
To prevent the problem, in the case of a computer system, there have been developed several methods for allowing only a specified person to access to the computer system. The methods may be classified into a method using an ID, a password, a certification key, etc. and a method using a biological property. The biological property is comprised of a voice, a fingerprint, lines of a finger or a palm, a retinal pattern, etc.
The voice is a universal and simple means to express a human's intention. As technologies using the voice, there have been proposed a voice recognition system for perceiving the voice, a speaker recognition system for recognizing a speaker uttering the voice, etc.
In the speaker recognition system, a user does not need to use an ID and a password to prevent an illegal use. Further, only a sound card and a microphone, which are generally provided in a personal computer system, are adequate to perform the speaker recognition system. Furthermore, in the speaker recognition system, the personal computer system can be controlled to operate in response to the voice of a specified person.
The speaker recognition may be classified into speaker identification and speaker verification in terms of a recognition method. The speaker identification is to identify a speaker of an inputted voice, and the speaker verification is to accept or reject a speaker by verifying the voice of the speaker.
A general process of the speaker recognition will be described as follows.
First, if a speaker inputs his/her voice to a speaker recognition system in order to register himself/herself, a waveform of the inputted voice signal is represented as a spectrum. The spectrum is analyzed so as to pick out an isolated word, thereby sampling phonemes from the word. Herein, the phonemes are predetermined so as to be employed as a reference for recognizing the voice. Thereafter, the speaker recognition system makes a pattern for each phoneme of a speaker, and subsequently compares it with patterns of the predetermined phonemes, thereby learning the speaker's characteristics. If the learning is completed, the speaker's pattern is registered.
Later on, if a voice is newly inputted to the speaker recognition system, the speaker recognition system makes a pattern based on the new-inputted voice through the above analyzing process, and subsequently compares it with the voice pattern of the registered(background) speaker, thereby accepting or rejecting the speaker.
In the conventional speaker recognition system, a new-made pattern is compared to the voice pattern of the registered speaker stored in a database. However, the voice stored in the database is recorded under ideal conditions such as little noise, a highly efficient microphone, the uniform loudness of voice, etc., and therefore the voice stored in the database indicates only a special example of the actual voice.
In the case of inputting the voice uttered in the conditions different from the voice stored in the database, the performance of the voice recognition system is influenced. Particularly, the loudness of voice makes a significant influence on the performance of the system.
Thus, in the voice recognition system, it is necessary to provide voice learning and speaker verification in consideration of the influence of the loudness of voice.